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*The author of this computation has been verified*

R Software Module

Patrick.Wessarwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Tue, 14 Dec 2010 17:05:18 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t1292346460sgx5kyh10prpl47.htm/, Retrieved Thu, 02 May 2024 22:31:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109902, Retrieved Thu, 02 May 2024 22:31:14 +0000

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No (this computation is public)

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Estimated Impact

135

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
-   PD    [Kendall tau Correlation Matrix] [Blog 1] [2010-12-14 17:05:18] [47bfda5353cd53c1cf7ea7aa9038654a] [Current]
-           [Kendall tau Correlation Matrix] [Pearson Correlati...] [2010-12-14 20:42:33] [1afa3497b02a8d7c9f6727c1b17b89b2] 

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Dataseries X:

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3,18	0,22	6,62	3,64
3,14	0,22	6,56	3,62
3,02	0,23	6,59	3,61
3,02	0,24	6,56	3,6
3,03	0,25	6,57	3,6
3,04	0,25	6,62	3,63
3,09	0,24	6,69	3,59
3,06	0,24	6,69	3,55
3,06	0,22	6,64	3,54
3,09	0,21	6,6	3,53
3,11	0,21	6,66	3,53
3,1	0,21	6,62	3,53
3,09	0,2	6,64	3,52
3,19	0,2	6,64	3,52
3,22	0,2	6,73	3,48
3,22	0,2	6,73	3,49
3,25	0,2	6,69	3,47
3,25	0,2	6,78	3,46
3,27	0,2	6,77	3,4
3,28	0,2	6,8	3,36
3,24	0,2	6,8	3,3
3,23	0,2	6,74	3,28
3,2	0,2	6,84	3,28
3,19	0,2	6,83	3,24
3,23	0,2	6,89	3,23
3,19	0,2	6,9	3,2
3,16	0,2	6,86	3,15
3,11	0,2	6,78	3,1
3,11	0,2	6,82	3,07
3,07	0,2	6,81	3,03
3,05	0,21	6,81	2,96
3	0,2	6,78	2,88
2,95	0,2	6,79	2,83
2,9	0,19	6,83	2,8
2,88	0,18	6,9	2,8
2,9	0,18	6,79	2,79
2,89	0,17	6,88	2,79
2,89	0,17	6,89	2,78
2,91	0,17	6,91	2,79
2,9	0,17	6,93	2,78
2,9	0,17	6,89	2,78
2,88	0,16	7	2,74
2,83	0,16	7,01	2,71
2,8	0,16	7,15	2,69
2,77	0,16	7,25	2,68
2,78	0,16	7,33	2,68
2,75	0,16	7,39	2,68
2,74	0,15	7,38	2,69
2,73	0,15	7,38	2,68
2,69	0,15	7,35	2,69
2,67	0,15	7,38	2,68
2,66	0,15	7,34	2,68
2,67	0,16	7,25	2,63
2,65	0,15	7,07	2,58
2,64	0,15	6,73	2,52
2,63	0,15	6,56	2,5

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109902&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109902&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109902&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Correlations for all pairs of data series (method=pearson)
	Mayonaise	Eieren	Olijfolie	Mosterd
Mayonaise	1	0.745	-0.653	0.828
Eieren	0.745	1	-0.773	0.897
Olijfolie	-0.653	-0.773	1	-0.728
Mosterd	0.828	0.897	-0.728	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Mayonaise & Eieren & Olijfolie & Mosterd \tabularnewline
Mayonaise & 1 & 0.745 & -0.653 & 0.828 \tabularnewline
Eieren & 0.745 & 1 & -0.773 & 0.897 \tabularnewline
Olijfolie & -0.653 & -0.773 & 1 & -0.728 \tabularnewline
Mosterd & 0.828 & 0.897 & -0.728 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109902&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Mayonaise[/C][C]Eieren[/C][C]Olijfolie[/C][C]Mosterd[/C][/ROW]
[ROW][C]Mayonaise[/C][C]1[/C][C]0.745[/C][C]-0.653[/C][C]0.828[/C][/ROW]
[ROW][C]Eieren[/C][C]0.745[/C][C]1[/C][C]-0.773[/C][C]0.897[/C][/ROW]
[ROW][C]Olijfolie[/C][C]-0.653[/C][C]-0.773[/C][C]1[/C][C]-0.728[/C][/ROW]
[ROW][C]Mosterd[/C][C]0.828[/C][C]0.897[/C][C]-0.728[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109902&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109902&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
	Mayonaise	Eieren	Olijfolie	Mosterd
Mayonaise	1	0.745	-0.653	0.828
Eieren	0.745	1	-0.773	0.897
Olijfolie	-0.653	-0.773	1	-0.728
Mosterd	0.828	0.897	-0.728	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Mayonaise;Eieren	0.7446	0.697	0.5209
p-value	(0)	(0)	(0)
Mayonaise;Olijfolie	-0.653	-0.5047	-0.3634
p-value	(0)	(1e-04)	(1e-04)
Mayonaise;Mosterd	0.8279	0.7564	0.5889
p-value	(0)	(0)	(0)
Eieren;Olijfolie	-0.7726	-0.7807	-0.6877
p-value	(0)	(0)	(0)
Eieren;Mosterd	0.8973	0.9464	0.8457
p-value	(0)	(0)	(0)
Olijfolie;Mosterd	-0.7284	-0.7929	-0.6903
p-value	(0)	(0)	(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Mayonaise;Eieren & 0.7446 & 0.697 & 0.5209 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Mayonaise;Olijfolie & -0.653 & -0.5047 & -0.3634 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
Mayonaise;Mosterd & 0.8279 & 0.7564 & 0.5889 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Eieren;Olijfolie & -0.7726 & -0.7807 & -0.6877 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Eieren;Mosterd & 0.8973 & 0.9464 & 0.8457 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Olijfolie;Mosterd & -0.7284 & -0.7929 & -0.6903 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109902&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Mayonaise;Eieren[/C][C]0.7446[/C][C]0.697[/C][C]0.5209[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Mayonaise;Olijfolie[/C][C]-0.653[/C][C]-0.5047[/C][C]-0.3634[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Mayonaise;Mosterd[/C][C]0.8279[/C][C]0.7564[/C][C]0.5889[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Eieren;Olijfolie[/C][C]-0.7726[/C][C]-0.7807[/C][C]-0.6877[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Eieren;Mosterd[/C][C]0.8973[/C][C]0.9464[/C][C]0.8457[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Olijfolie;Mosterd[/C][C]-0.7284[/C][C]-0.7929[/C][C]-0.6903[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109902&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109902&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Mayonaise;Eieren	0.7446	0.697	0.5209
p-value	(0)	(0)	(0)
Mayonaise;Olijfolie	-0.653	-0.5047	-0.3634
p-value	(0)	(1e-04)	(1e-04)
Mayonaise;Mosterd	0.8279	0.7564	0.5889
p-value	(0)	(0)	(0)
Eieren;Olijfolie	-0.7726	-0.7807	-0.6877
p-value	(0)	(0)	(0)
Eieren;Mosterd	0.8973	0.9464	0.8457
p-value	(0)	(0)	(0)
Olijfolie;Mosterd	-0.7284	-0.7929	-0.6903
p-value	(0)	(0)	(0)

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = pearson ;

Parameters (R input):

par1 = pearson ;

R code (references can be found in the software module):

panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')

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Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code